WEEK 8: FUNCTIONAL PROGRAMMING
Monday, February 27th
Today we will…
- Questions about Lab 7
- Project Proposal – Data
- Mini lecture on text material1
- Review vectorization
- The
map()family
- PA 8: The 12 Days of Christmas Starter Functions
Iteration
Repeating the same operation multiple times
Vectorized Functions
Operations in R are typically vectorized
By default, the functions operate on vectors of values rather than a single value.
[1] -4.0 -3.5 -3.0 -2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0
[16] 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0 10.5
[31] 11.0 11.5 12.0 [1] 4.0 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 0.5 1.0 1.5 2.0 2.5 3.0
[16] 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0 10.5
[31] 11.0 11.5 12.0Is every function vectorized? Short answer, no.
For example, if the function you’ve written makes use of if() statements, your function cannot operate on vectors.
pos_neg_zero <- function(x){
stopifnot(is.numeric(x))
if(x > 0){
return("Greater than 0!")
} else if (x < 0){
return("Less than 0!")
} else {
return("Equal to 0!")
}
}
x <- seq(from = -4, to = 4, by = 1)
pos_neg_zero(x)Error in if (x > 0) {: the condition has length > 1This error means that the if(x > 0) condition can only be checked for something of length 1.
pos_neg_zero <- function(x){
stopifnot(is.numeric(x))
state <- case_when(x > 0 ~ "Greater than 0!",
x < 0 ~ "Less than 0!",
TRUE ~ "Equal to 0!")
return(state)
}
x <- seq(from = -4, to = 4, by = 1)
pos_neg_zero(x)[1] "Less than 0!" "Less than 0!" "Less than 0!" "Less than 0!"
[5] "Equal to 0!" "Greater than 0!" "Greater than 0!" "Greater than 0!"
[9] "Greater than 0!"When can’t you vectorize your function?
Applying typeof() to a single variable tells us the datatype of that column.
Applying typeof() to every variable in the data frame returns an object structure of the penguins data frame, not the datatype of its columns.
What can we do instead?
Your good CSC 101 friend, the for() loop
data_type <- rep(NA, length = ncol(penguins))
for(i in 1:ncol(penguins)){
data_type[i] <- typeof(penguins[[i]])
}
# format table nicely
tibble(column = names(penguins),
type = data_type) %>%
pivot_wider(names_from = column,
values_from = type) %>%
knitr::kable()| species | island | bill_length_mm | bill_depth_mm | flipper_length_mm | body_mass_g | sex | year |
|---|---|---|---|---|---|---|---|
| integer | integer | double | double | integer | integer | integer | integer |
… but we don’t really need this in R because it is a functional programming language
Remember across()
We have continually called on the across() function to reduce repetition in our code, when performing the same operation(s) on multiple columns.
# A tibble: 1 × 8
species island bill_length_mm bill_depth_mm flipper_leng…¹ body_…² sex year
<int> <int> <int> <int> <int> <int> <int> <int>
1 0 0 2 2 2 2 11 0
# … with abbreviated variable names ¹flipper_length_mm, ²body_mass_gUgh. but across() uses a for() loop “behind the scenes”
for (j in seq_fns) {
fn <- fns[[j]]
out[[k]] <- fn(col, ...)
k <- k + 1L
Functional Programming
To understand computations in R, two slogans are helpful:
Everything that exists is an object.
Everything that happens is a function call.
John Chambers
Functional Programming
The big picture: Using functions as arguments to functions
Note
There are a slew of apply() functions you will likely come across, but we will instead focus on the purrr package and map() family of functions.
The best option: library(purrr)
The main goal of using purrr functions (instead of for loops) is to break common list manipulation challenges into smaller and independent pieces. This strategy involves two steps, each of which scales down the problem:
Solving the problem for a single element of a list. Once we have solved that problem,
purrrtakes care of generalizing the solution to every element in the list.Breaking a complex problem down into smaller sub-problems that allow us to advance towards a solution. With
purrr, we get many small pieces that we can compose together with the pipe (|>).
This scaling-down strategy makes it easier to solve new problems and to understand our solutions to old problems when we re-read older code.
Introduction to map()
map iterates through each item in the list and applies a function.
map() family
map_xxx variants allow you to specify the type of output you want back
map()creates a listmap_chr()creates a logical vectormap_lgl()creates an integer vectormap_int()creates a double vectormap_dbl()creates a character vector
map2_chr()map2_lgl()map2_int()map2_dbl()pmap()
Example – map() + penguins
species island bill_length_mm bill_depth_mm
0 0 2 2
flipper_length_mm body_mass_g sex year
2 2 11 0 - Note the
~and the.x, just like inacross()!
Example – map() + penguins
# A tibble: 344 × 8
species island bill_length_mm[,1] bill_dep…¹ flipp…² body_…³ sex year[…⁴
<fct> <fct> <dbl> <dbl> <dbl> <dbl> <fct> <dbl>
1 Adelie Torgersen -0.883 0.784 -1.42 -0.563 male -1.26
2 Adelie Torgersen -0.810 0.126 -1.06 -0.501 fema… -1.26
3 Adelie Torgersen -0.663 0.430 -0.421 -1.19 fema… -1.26
4 Adelie Torgersen NA NA NA NA <NA> -1.26
5 Adelie Torgersen -1.32 1.09 -0.563 -0.937 fema… -1.26
6 Adelie Torgersen -0.847 1.75 -0.776 -0.688 male -1.26
7 Adelie Torgersen -0.920 0.329 -1.42 -0.719 fema… -1.26
8 Adelie Torgersen -0.865 1.24 -0.421 0.590 male -1.26
9 Adelie Torgersen -1.80 0.480 -0.563 -0.906 <NA> -1.26
10 Adelie Torgersen -0.352 1.54 -0.776 0.0602 <NA> -1.26
# … with 334 more rows, and abbreviated variable names ¹bill_depth_mm[,1],
# ²flipper_length_mm[,1], ³body_mass_g[,1], ⁴year[,1]$species
[1] Adelie Adelie Adelie Adelie Adelie Adelie Adelie
[8] Adelie Adelie Adelie Adelie Adelie Adelie Adelie
[15] Adelie Adelie Adelie Adelie Adelie Adelie Adelie
[22] Adelie Adelie Adelie Adelie Adelie Adelie Adelie
[29] Adelie Adelie Adelie Adelie Adelie Adelie Adelie
[36] Adelie Adelie Adelie Adelie Adelie Adelie Adelie
[43] Adelie Adelie Adelie Adelie Adelie Adelie Adelie
[50] Adelie Adelie Adelie Adelie Adelie Adelie Adelie
[57] Adelie Adelie Adelie Adelie Adelie Adelie Adelie
[64] Adelie Adelie Adelie Adelie Adelie Adelie Adelie
[71] Adelie Adelie Adelie Adelie Adelie Adelie Adelie
[78] Adelie Adelie Adelie Adelie Adelie Adelie Adelie
[85] Adelie Adelie Adelie Adelie Adelie Adelie Adelie
[92] Adelie Adelie Adelie Adelie Adelie Adelie Adelie
[99] Adelie Adelie Adelie Adelie Adelie Adelie Adelie
[106] Adelie Adelie Adelie Adelie Adelie Adelie Adelie
[113] Adelie Adelie Adelie Adelie Adelie Adelie Adelie
[120] Adelie Adelie Adelie Adelie Adelie Adelie Adelie
[127] Adelie Adelie Adelie Adelie Adelie Adelie Adelie
[134] Adelie Adelie Adelie Adelie Adelie Adelie Adelie
[141] Adelie Adelie Adelie Adelie Adelie Adelie Adelie
[148] Adelie Adelie Adelie Adelie Adelie Gentoo Gentoo
[155] Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo
[162] Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo
[169] Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo
[176] Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo
[183] Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo
[190] Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo
[197] Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo
[204] Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo
[211] Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo
[218] Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo
[225] Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo
[232] Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo
[239] Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo
[246] Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo
[253] Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo
[260] Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo
[267] Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo Gentoo
[274] Gentoo Gentoo Gentoo Chinstrap Chinstrap Chinstrap Chinstrap
[281] Chinstrap Chinstrap Chinstrap Chinstrap Chinstrap Chinstrap Chinstrap
[288] Chinstrap Chinstrap Chinstrap Chinstrap Chinstrap Chinstrap Chinstrap
[295] Chinstrap Chinstrap Chinstrap Chinstrap Chinstrap Chinstrap Chinstrap
[302] Chinstrap Chinstrap Chinstrap Chinstrap Chinstrap Chinstrap Chinstrap
[309] Chinstrap Chinstrap Chinstrap Chinstrap Chinstrap Chinstrap Chinstrap
[316] Chinstrap Chinstrap Chinstrap Chinstrap Chinstrap Chinstrap Chinstrap
[323] Chinstrap Chinstrap Chinstrap Chinstrap Chinstrap Chinstrap Chinstrap
[330] Chinstrap Chinstrap Chinstrap Chinstrap Chinstrap Chinstrap Chinstrap
[337] Chinstrap Chinstrap Chinstrap Chinstrap Chinstrap Chinstrap Chinstrap
[344] Chinstrap
Levels: Adelie Chinstrap Gentoo
$island
[1] Torgersen Torgersen Torgersen Torgersen Torgersen Torgersen Torgersen
[8] Torgersen Torgersen Torgersen Torgersen Torgersen Torgersen Torgersen
[15] Torgersen Torgersen Torgersen Torgersen Torgersen Torgersen Biscoe
[22] Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe
[29] Biscoe Biscoe Dream Dream Dream Dream Dream
[36] Dream Dream Dream Dream Dream Dream Dream
[43] Dream Dream Dream Dream Dream Dream Dream
[50] Dream Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe
[57] Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe
[64] Biscoe Biscoe Biscoe Biscoe Biscoe Torgersen Torgersen
[71] Torgersen Torgersen Torgersen Torgersen Torgersen Torgersen Torgersen
[78] Torgersen Torgersen Torgersen Torgersen Torgersen Torgersen Torgersen
[85] Dream Dream Dream Dream Dream Dream Dream
[92] Dream Dream Dream Dream Dream Dream Dream
[99] Dream Dream Biscoe Biscoe Biscoe Biscoe Biscoe
[106] Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe
[113] Biscoe Biscoe Biscoe Biscoe Torgersen Torgersen Torgersen
[120] Torgersen Torgersen Torgersen Torgersen Torgersen Torgersen Torgersen
[127] Torgersen Torgersen Torgersen Torgersen Torgersen Torgersen Dream
[134] Dream Dream Dream Dream Dream Dream Dream
[141] Dream Dream Dream Dream Dream Dream Dream
[148] Dream Dream Dream Dream Dream Biscoe Biscoe
[155] Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe
[162] Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe
[169] Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe
[176] Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe
[183] Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe
[190] Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe
[197] Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe
[204] Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe
[211] Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe
[218] Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe
[225] Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe
[232] Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe
[239] Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe
[246] Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe
[253] Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe
[260] Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe
[267] Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe Biscoe
[274] Biscoe Biscoe Biscoe Dream Dream Dream Dream
[281] Dream Dream Dream Dream Dream Dream Dream
[288] Dream Dream Dream Dream Dream Dream Dream
[295] Dream Dream Dream Dream Dream Dream Dream
[302] Dream Dream Dream Dream Dream Dream Dream
[309] Dream Dream Dream Dream Dream Dream Dream
[316] Dream Dream Dream Dream Dream Dream Dream
[323] Dream Dream Dream Dream Dream Dream Dream
[330] Dream Dream Dream Dream Dream Dream Dream
[337] Dream Dream Dream Dream Dream Dream Dream
[344] Dream
Levels: Biscoe Dream Torgersen
$bill_length_mm
[,1]
[1,] -0.88320467
[2,] -0.80993901
[3,] -0.66340769
[4,] NA
[5,] -1.32279862
[6,] -0.84657184
[7,] -0.91983750
[8,] -0.86488825
[9,] -1.79902541
[10,] -0.35202864
[11,] -1.12131806
[12,] -1.12131806
[13,] -0.51687637
[14,] -0.97478674
[15,] -1.70744334
[16,] -1.34111504
[17,] -0.95647033
[18,] -0.26044656
[19,] -1.74407616
[20,] 0.38062795
[21,] -1.12131806
[22,] -1.13963448
[23,] -1.46932994
[24,] -1.04805240
[25,] -0.93815391
[26,] -1.57922843
[27,] -0.60845845
[28,] -0.62677486
[29,] -1.10300165
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[44,] 0.03261607
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[49,] -1.45101353
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[51,] -0.79162259
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[53,] -1.63417768
[54,] -0.35202864
[55,] -1.72575975
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[68,] -0.51687637
[69,] -1.46932994
[70,] -0.38866147
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[72,] -0.77330618
[73,] -0.79162259
[74,] 0.34399512
[75,] -1.54259560
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[80,] -0.33371222
[81,] -1.70744334
[82,] -0.18718091
[83,] -1.32279862
[84,] -1.61586126
[85,] -1.21290014
[86,] -0.48024354
[87,] -1.39606428
[88,] -1.28616579
[89,] -1.02973599
[90,] -0.91983750
[91,] -1.50596277
[92,] -0.51687637
[93,] -1.81734182
[94,] -0.79162259
[95,] -1.41438070
[96,] -0.57182562
[97,] -1.06636882
[98,] -0.66340769
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[101,] -1.63417768
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[104,] -1.12131806
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[106,] -0.77330618
[107,] -0.97478674
[108,] -1.04805240
[109,] -1.06636882
[110,] -0.13223166
[111,] -1.06636882
[112,] 0.30736229
[113,] -0.77330618
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[115,] -0.79162259
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[117,] -0.97478674
[118,] -1.21290014
[119,] -1.50596277
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[121,] -1.41438070
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[126,] -0.60845845
[127,] -0.93815391
[128,] -0.44361071
[129,] -0.90152108
[130,] 0.03261607
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[135,] -1.06636882
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[144,] -0.59014203
[145,] -1.21290014
[146,] -0.90152108
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[148,] -1.34111504
[149,] -1.45101353
[150,] -1.12131806
[151,] -1.45101353
[152,] -0.44361071
[153,] 0.39894437
[154,] 1.11328455
[155,] 0.87517115
[156,] 1.11328455
[157,] 0.67369059
[158,] 0.47221003
[159,] 0.27072946
[160,] 0.50884286
[161,] -0.11391525
[162,] 0.52715927
[163,] -0.55350920
[164,] 0.93012040
[165,] 0.28904588
[166,] 0.82022191
[167,] 0.34399512
[168,] 0.98506964
[169,] -0.35202864
[170,] 0.96675323
[171,] 0.41726078
[172,] 0.87517115
[173,] 1.14991738
[174,] 0.21578022
[175,] 0.47221003
[176,] 0.43557720
[177,] -0.18718091
[178,] 0.39894437
[179,] 0.10588173
[180,] 0.71032342
[181,] 0.78358908
[182,] 1.11328455
[183,] 0.61874135
[184,] -0.20549732
[185,] 0.21578022
[186,] 2.87166037
[187,] 0.94843681
[188,] 0.82022191
[189,] -0.24213015
[190,] 0.08756532
[191,] 0.01429966
[192,] 0.87517115
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[194,] 1.04001889
[195,] 0.25241305
[196,] 1.04001889
[197,] 1.20486662
[198,] -0.05896600
[199,] 0.28904588
[200,] 1.20486662
[201,] 0.17914739
[202,] 0.23409663
[203,] 0.49052644
[204,] 0.83853832
[205,] 0.21578022
[206,] 1.13160096
[207,] 0.47221003
[208,] 0.19746381
[209,] -0.02233317
[210,] 0.28904588
[211,] -0.13223166
[212,] 1.18655021
[213,] 0.25241305
[214,] 0.41726078
[215,] 0.32567871
[216,] 1.90089038
[217,] 0.34399512
[218,] 1.07665172
[219,] 0.41726078
[220,] 1.02170247
[221,] -0.07728242
[222,] 1.24149945
[223,] 0.69200701
[224,] 0.45389361
[225,] 0.78358908
[226,] 0.47221003
[227,] 0.45389361
[228,] 0.85685474
[229,] 0.65537418
[230,] 1.31476511
[231,] 0.23409663
[232,] 0.23409663
[233,] 0.94843681
[234,] 1.57119492
[235,] 0.63705776
[236,] 1.11328455
[237,] 0.17914739
[238,] 1.25981586
[239,] -0.09559883
[240,] 1.35139794
[241,] 0.65537418
[242,] 1.49792926
[243,] 0.65537418
[244,] 1.51624567
[245,] 0.28904588
[246,] 1.02170247
[247,] 0.10588173
[248,] 1.25981586
[249,] 1.00338606
[250,] 0.54547569
[251,] 0.82022191
[252,] 1.31476511
[253,] 0.83853832
[254,] 2.19395302
[255,] 0.60042493
[256,] 0.94843681
[257,] 0.61874135
[258,] 0.52715927
[259,] -0.40697788
[260,] 1.73604265
[261,] -0.11391525
[262,] 0.76527266
[263,] 1.20486662
[264,] 1.07665172
[265,] -0.07728242
[266,] 1.38803077
[267,] 0.41726078
[268,] 2.04742170
[269,] 0.10588173
[270,] 0.89348757
[271,] 0.60042493
[272,] NA
[273,] 0.52715927
[274,] 1.18655021
[275,] 0.23409663
[276,] 1.09496813
[277,] 0.47221003
[278,] 1.11328455
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[280,] 0.27072946
[281,] 1.60782775
[282,] 0.23409663
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[285,] 0.38062795
[286,] 1.35139794
[287,] 0.49052644
[288,] 1.42466360
[289,] 0.56379210
[290,] 1.47961284
[291,] 0.36231154
[292,] 1.20486662
[293,] 1.16823379
[294,] 2.57859773
[295,] 0.45389361
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[300,] 1.22318303
[301,] 0.50884286
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[308,] 1.88257397
[309,] -0.26044656
[310,] 1.29644869
[311,] 1.05833530
[312,] 0.65537418
[313,] 0.67369059
[314,] 1.47961284
[315,] 0.54547569
[316,] 1.75435906
[317,] 0.93012040
[318,] 0.41726078
[319,] 1.27813228
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attr(,"scaled:center")
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attr(,"scaled:scale")
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$body_mass_g
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$sex
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[11] <NA> <NA> female male male female female male female male
[21] female male female male male female male female female male
[31] female male female male female male male female female male
[41] female male female male female male male <NA> female male
[51] female male female male female male female male female male
[61] female male female male female male female male female male
[71] female male female male female male female male female male
[81] female male female male female male male female male female
[91] female male female male female male female male female male
[101] female male female male female male female male female male
[111] female male female male female male female male female male
[121] female male female male female male female male female male
[131] female male female male female male female male female male
[141] female male female male female male male female female male
[151] female male female male female male male female female male
[161] female male female male female male female male female male
[171] female male male female female male female male <NA> male
[181] female male male female female male female male female male
[191] female male female male female male male female female male
[201] female male female male female male female male female male
[211] female male female male female male female male <NA> male
[221] female male female male male female female male female male
[231] female male female male female male female male female male
[241] female male female male female male female male male female
[251] female male female male female male <NA> male female male
[261] female male female male female male female male <NA> male
[271] female <NA> female male female male female male male female
[281] male female female male female male female male female male
[291] female male male female female male female male female male
[301] female male female male female male female male female male
[311] male female female male female male male female male female
[321] female male female male male female female male female male
[331] female male female male male female male female female male
[341] female male male female
Levels: female male
$year
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[228,] -0.03552216
[229,] -0.03552216
[230,] -0.03552216
[231,] -0.03552216
[232,] -0.03552216
[233,] 1.18644003
[234,] 1.18644003
[235,] 1.18644003
[236,] 1.18644003
[237,] 1.18644003
[238,] 1.18644003
[239,] 1.18644003
[240,] 1.18644003
[241,] 1.18644003
[242,] 1.18644003
[243,] 1.18644003
[244,] 1.18644003
[245,] 1.18644003
[246,] 1.18644003
[247,] 1.18644003
[248,] 1.18644003
[249,] 1.18644003
[250,] 1.18644003
[251,] 1.18644003
[252,] 1.18644003
[253,] 1.18644003
[254,] 1.18644003
[255,] 1.18644003
[256,] 1.18644003
[257,] 1.18644003
[258,] 1.18644003
[259,] 1.18644003
[260,] 1.18644003
[261,] 1.18644003
[262,] 1.18644003
[263,] 1.18644003
[264,] 1.18644003
[265,] 1.18644003
[266,] 1.18644003
[267,] 1.18644003
[268,] 1.18644003
[269,] 1.18644003
[270,] 1.18644003
[271,] 1.18644003
[272,] 1.18644003
[273,] 1.18644003
[274,] 1.18644003
[275,] 1.18644003
[276,] 1.18644003
[277,] -1.25748435
[278,] -1.25748435
[279,] -1.25748435
[280,] -1.25748435
[281,] -1.25748435
[282,] -1.25748435
[283,] -1.25748435
[284,] -1.25748435
[285,] -1.25748435
[286,] -1.25748435
[287,] -1.25748435
[288,] -1.25748435
[289,] -1.25748435
[290,] -1.25748435
[291,] -1.25748435
[292,] -1.25748435
[293,] -1.25748435
[294,] -1.25748435
[295,] -1.25748435
[296,] -1.25748435
[297,] -1.25748435
[298,] -1.25748435
[299,] -1.25748435
[300,] -1.25748435
[301,] -1.25748435
[302,] -1.25748435
[303,] -0.03552216
[304,] -0.03552216
[305,] -0.03552216
[306,] -0.03552216
[307,] -0.03552216
[308,] -0.03552216
[309,] -0.03552216
[310,] -0.03552216
[311,] -0.03552216
[312,] -0.03552216
[313,] -0.03552216
[314,] -0.03552216
[315,] -0.03552216
[316,] -0.03552216
[317,] -0.03552216
[318,] -0.03552216
[319,] -0.03552216
[320,] -0.03552216
[321,] 1.18644003
[322,] 1.18644003
[323,] 1.18644003
[324,] 1.18644003
[325,] 1.18644003
[326,] 1.18644003
[327,] 1.18644003
[328,] 1.18644003
[329,] 1.18644003
[330,] 1.18644003
[331,] 1.18644003
[332,] 1.18644003
[333,] 1.18644003
[334,] 1.18644003
[335,] 1.18644003
[336,] 1.18644003
[337,] 1.18644003
[338,] 1.18644003
[339,] 1.18644003
[340,] 1.18644003
[341,] 1.18644003
[342,] 1.18644003
[343,] 1.18644003
[344,] 1.18644003
attr(,"scaled:center")
[1] 2008.029
attr(,"scaled:scale")
[1] 0.8183559
PA 8: The 12 Days of Christmas
A (boring) Example
Timothee Chalamet’s Statistics
A (better) Example – 99 Bottles of Beer
99 bottles of beer on the wall, 99 bottles of beer. Take one down, pass it around, 98 bottles of beer on the wall…
bottles_lyrics <- function(n){
lyrics <- glue::glue("{n} bottles of beer on the wall, {n} bottles of beer \nTake one down, pass it around, {n -1} bottles of beer on the wall")
return(lyrics)
}
bottles_lyrics(3)3 bottles of beer on the wall, 3 bottles of beer
Take one down, pass it around, 2 bottles of beer on the wallbottles_song <- function(n){
song <- map_chr(n:0, bottles_lyrics)
return(
glue::glue("{song}")
)
}
bottles_song(3)3 bottles of beer on the wall, 3 bottles of beer
Take one down, pass it around, 2 bottles of beer on the wall
2 bottles of beer on the wall, 2 bottles of beer
Take one down, pass it around, 1 bottles of beer on the wall
1 bottles of beer on the wall, 1 bottles of beer
Take one down, pass it around, 0 bottles of beer on the wall
0 bottles of beer on the wall, 0 bottles of beer
Take one down, pass it around, -1 bottles of beer on the wallNo more bottles of beer on the wall, no more bottles of beer.
Go to the store and buy some more, 99 bottles of beer on the wall…
bottles_lyrics <- function(n){
if(n == 0){
lyrics <- glue::glue("No more bottles of beer on the wall, no more bottles of beer. \nGo to the store and buy some more, 99 bottles of beer on the wall")
} else{
lyrics <- glue::glue("{n} bottles of beer on the wall, {n} bottles of beer \nTake one down, pass it around, {n -1} bottles of beer on the wall")
}
return(lyrics)
}4 bottles of beer on the wall, 4 bottles of beer
Take one down, pass it around, 3 bottles of beer on the wall
3 bottles of beer on the wall, 3 bottles of beer
Take one down, pass it around, 2 bottles of beer on the wall
2 bottles of beer on the wall, 2 bottles of beer
Take one down, pass it around, 1 bottles of beer on the wall
1 bottles of beer on the wall, 1 bottles of beer
Take one down, pass it around, 0 bottles of beer on the wall
No more bottles of beer on the wall, no more bottles of beer.
Go to the store and buy some more, 99 bottles of beer on the wallTo do…
- PA 8: The 12 Days of Christmas Starter Functions
- Due Wednesday 3/1 at 8am
- Project Proposal – Data
- Due Sunday 3/5 at 11:59pm
Wednesday, March 1st
Today we will…
- Challenge 7: Incorporating Multiple Inputs
To do…
- Lab 8: The 12 Days of Christmas Sing the Full Song
- Due Friday 3/3 at 11:59pm
- Challenge 8: Styling Your Song
- Due Saturday 3/4 at 11:59pm
- Read Chapter 9: Regression & Simulation
- Check-in 9.1 & 9.2 due Monday 3/6 at 8am